Sample based tone mapping method for high dynamic range images

ABSTRACT

The disclosure relates to adjusting intensities of images. The method includes receiving information identifying of a plurality of regions within an image; receiving an intensity adjustment of at least one of the plurality of regions; adjusting the intensities of the at least one plurality of regions based on the received intensity adjustment; interconnecting at least two of the plurality of regions by applying a two-dimensional method; generating intensity adjustments for at least one pixel outside the plurality of regions based on the received intensity adjustment of at least one of the plurality of regions and the interconnection of at least two of the plurality of regions; and applying the generated intensity adjustments to the image.

BACKGROUND

High dynamic range images have a greater dynamic range of luminancebetween light and dark areas of a scene than normal images. This permitsa more accurate representation of the wide range of intensity levelsfound in real scenes ranging from direct sunlight to shadows. However,high dynamic range images may not be directly viewed on an averagedisplay device due to limitations of the display device.

SUMMARY

A method is described for adjusting intensities of images. The methodincludes receiving information identifying of a plurality of regionswithin an image; receiving an intensity adjustment of at least one ofthe plurality of regions; adjusting the intensities of the at least oneplurality of regions based on the received intensity adjustment;interconnecting at least two of the plurality of regions by applying atwo-dimensional method; generating intensity adjustments for at leastone pixel outside the plurality of regions based on the receivedintensity adjustment of at least one of the plurality of regions and theinterconnection of at least two of the plurality of regions; andapplying the generated intensity adjustments to the image.

Furthermore, the present disclosure describes an apparatus for intensitymapping of image data. The apparatus includes a receiver that receivesinformation identifying of a plurality of regions within an image andreceiving an intensity adjustment of at least one of the plurality ofregions; an adjustment unit that adjusts the intensities of the at leastone plurality of regions based on the received intensity adjustment; ainterconnection unit that interconnects at least two of the plurality ofregions by applying a two-dimensional method; an intensity generationunit that generates intensity adjustments for at least one pixel outsidethe plurality of regions based on the received intensity adjustment ofat least one of the plurality of regions and the interconnection of atleast two of the plurality of regions; and an intensity application unitthat applies the generated intensity adjustments to the image.

The foregoing is a summary and thus contains, by necessity,simplifications, generalization, and omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, features, and advantages of the devices and/or processes and/orother subject matter described herein will become apparent in theteachings set forth herein. The summary is provided to introduce aselection of concepts in a simplified form that are further describedbelow in the Detailed Description. This summary is not intended toidentify key features or essential features of the claimed subjectmatter, nor is it intended to be used as an aid in determining the scopeof the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of the present disclosure will becomemore fully apparent from the following description and appended claims,taken in conjunction with the accompanying drawings. Understanding thatthese drawings depict only several embodiments in accordance with thedisclosure and are, therefore, not to be considered limiting of itsscope, the disclosure will be described with additional specificity anddetail through use of the accompanying drawings.

FIG. 1 is a block diagram illustrating an example of a configuration ofa computing device arranged to process images, according to an exampleembodiment;

FIG. 2 is a block diagram illustrating an example of a configuration ofan application within a computing device arranged to process images,according to an example embodiment;

FIG. 3 is a flow diagram illustrating a method for processing images,according to an example embodiment; and

FIGS. 4A-4C is a diagram illustrating an example of image processingaccording to an example embodiment.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe Figures, can be arranged, substituted, combined, and designed in awide variety of different configurations, all of which are explicitlycontemplated and make part of this disclosure.

The present disclosure is directed to, inter alia, methods, apparatus,computer programs and systems for processing image data. Specifically,image data is processed by receiving information identifying of aplurality of regions within an image; receiving an intensity adjustmentof at least one of the plurality of regions; adjusting the intensitiesthe at least one plurality of regions based on the received intensityadjustment; interconnecting at least two of the plurality of regions byapplying a two-dimensional method; generating intensity adjustments forat least one pixel outside the plurality of regions based on thereceived intensity adjustment of at least one of the plurality ofregions and the interconnection of at least two of the plurality ofregions; and applying the generated intensity adjustments to the image.

This disclosure provides a new intensity mapping algorithm on convertinghigh dynamic images to regular low dynamic range images. Different fromtraditional intensity mapping methods, in the present disclosure a usercan directly work on an original high dynamic range image, or on a highdynamic range image whose intensity has been adjusted, and select a fewlocations to manually adjust the output intensity of the correspondingpixels, (e.g. pre-define the tone mapping results of the selectedlocations, which will become the pre-condition, i.e. input parameters,of the following processing). The system may compute the output pixelintensity of all remaining image pixels outside the selected areas basedon the manual adjusting result. Therefore, the intensity of the inputhigh dynamic range image is “tone mapping” according to the samplesgiven by the users.

The use of the term “image” in this disclosure is not intended belimited to a particular file type or data format. Instead, the term“image” as used in this disclosure may encompass content from any imagefile type or data format (JPEG, BMP, etc.), any graphically rendereddocument (e.g., a webpage or HTML document), a computer-aided design(CAD) application, scanned photographs or documents (e.g., in PDFformat), or any other type of computer-generated image.

FIG. 1 is a diagram illustrating a system environment in which thefeatures disclosed herein may be implemented. In a very basicconfiguration 101, computing device 120 typically includes one or moreprocessors 110 and system memory 120. A memory bus 130 can be used forcommunicating between the processor 110 and the system memory 120.

Depending on the desired configuration, processor 110 can be of any typeincluding but not limited to a microprocessor (μP), a microcontroller(μC), a digital signal processor (DSP), or any combination thereof.Processor 110 can include one more levels of caching, such as a levelone cache 111 and a level two cache 112, a processor core 113, andregisters 114. The processor core 113 can include an arithmetic logicunit (ALU), a floating point unit (FPU), a digital signal processingcore (DSP Core), or any combination thereof. A memory controller 115 canalso be used with the processor 110, or in some implementations thememory controller 115 can be an internal part of the processor 110.

Depending on the desired configuration, the system memory 120 can be ofany type including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. System memory 120 typically includes an operating system 121,one or more applications 122, and program data 124. Application 122 mayinclude an image processing algorithm 123 that is arranged to processoriginal image data. Program data 124 may include data 125 that definescertain variable parameters (e.g., user-defined parameters), and/orcertain rules, algorithms, and/or compression ratios for processingimage data.

Referring again to FIG. 1, computing device 120 can have additionalfeatures or functionality, and additional interfaces to facilitatecommunications between the basic configuration 101 and any requireddevices and interfaces. For example, a bus/interface controller 140 canbe used to facilitate communications between the basic configuration 101and one or more data storage devices 150 via a storage interface bus141. The data storage devices 150 can be removable storage devices 151,non-removable storage devices 152, or a combination thereof. Examples ofremovable storage and non-removable storage devices include magneticdisk devices such as flexible disk drives and hard-disk drives (HDD),optical disk drives such as compact disk (CD) drives or digitalversatile disk (DVD) drives, solid state drives (SSD), and tape drivesto name a few. Example computer storage media can include volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information, such as computer readableinstructions, data structures, program modules, or other data.

System memory 120, removable storage 151 and non-removable storage 152are all examples of computer storage media. Computer storage mediaincludes, but is not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology, CD-ROM, digital versatile disks (DVD) or otheroptical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bycomputing device 120. Any such computer storage media can be part ofdevice 120.

Computing device 120 can also include an interface bus 142 forfacilitating communication from various interface devices (e.g., outputinterfaces, peripheral interfaces, and communication interfaces) to thebasic configuration 101 via the bus/interface controller 140. Exampleoutput devices 160 include a graphics processing unit 161 which may beconfigured to communicate to the display device 130, and an audioprocessing unit 162 which may be configured to communicate to speakers,via one or more A/V ports 163. Example peripheral interfaces 170 includea serial interface controller 171 or a parallel interface controller172, which can be configured to communicate with external devices suchas input devices (e.g., keyboard, mouse, pen, voice input device, touchinput device, etc.) or other peripheral devices (e.g., printer, scanner,etc.) via one or more I/O ports 173. An example communication device 180includes a network controller 181, which can be arranged to facilitatecommunications with one or more other computing devices 190 over anetwork communication via one or more communication ports 182. Thecommunication connection is one example of a communication media.Communication media may typically be embodied by computer readableinstructions, data structures, program modules, or other data in amodulated data signal, such as a carrier wave or other transportmechanism, and includes any information delivery media. A “modulateddata signal” can be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media can includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), infrared (IR) andother wireless media. The term computer readable media as used hereincan include both storage media and communication media.

Computing device 100 can be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. Computing device 100 can also be implemented as a personalcomputer including both laptop computer and non-laptop computerconfigurations.

FIG. 2 is a block diagram block diagram illustrating an example of aconfiguration of an application within a computing device arranged toprocess images, according to an example embodiment. Application 122 mayinclude receiving unit 202, adjustment unit 204, interconnection unit206, intensity generation unit 208 and intensity application unit 210.

Receiving unit 202 may receive or access an image from storage devices150, from peripheral interfaces 170, etc. The image may be an originalimage A. A tone mapping algorithm may be applied to original image Aresulting in image A′. In addition, or alternatively, the original imageA may have an intensity adjustment applied thereto using a tone mappingmethod resulting in image A′. The intensity adjustment may be, forexample, i) Photographic Tone Reproduction for Digital Images ErikReinhard, Michael Stark, Peter Shirley, Jim Ferwerda ACM SIGGRAPH 2002;ii) Fast Bilateral Filtering for the Display of High Dynamic RangeImages Frédo Durand, Julie Dorsey ACM SIGGRAPH 2002; iii) GradientDomain High Dynamic Range Compression Raanan Fattal, Dani Lischinski,Michael Werman ACM SIGGRAPH 2002, etc.

The receiving unit 202 further receives information identifying aplurality of regions, i.e., 3, 4, 5, 6, etc., within the received image.The information identifying a plurality of regions may be received atperipheral interfaces 170, received from storage devices 150, etc. Itmay be appreciated that the higher the number of selected areas, themore advantageous the result is.

The selected regions may be any shape such as a circle, a square, anirregular shape, etc. The region may include a group of pixels. The sizeof the region may vary, may be predetermined, etc. The region may beselected, i.e., by using brush tool, line tool, etc., provided by a userinterface application providing within computing device 100. Inaddition, one or more selected regions may touch one or more otherselected regions or may not touch any other selected region.

Still further, the receiving unit 202 receives information relating toan intensity adjustment with respect to each region identified in theimage. The information identifying intensity adjustment of a pluralityof regions may be received at peripheral interfaces 170, received fromstorage devices 150, etc.

The information identifying intensity adjustment of each of theplurality of identified regions may not only identify an adjustment ofpixel intensity of the selected regions, but may also, alternatively,include additional information identifying the adjustment of the pixelintensity of the identified regions' neighborhood points on the image.

Adjustment unit 204 adjusts the intensity of the identified regionsbased on the received information identifying the adjustment of theidentified region thereby resulting in image A″. The adjustment may be alinear or a non-linear adjustment. For example, interpolation may bebased on Voronoi triangulation. The adjustment may not include themanually adjusted pixel intensities. The manual adjusted pixelintensities may be used input for the interconnection unit 2076, theintensity generation unit 208 and the intensity application unit 210 asdiscussed herein.

Interconnection unit 206 interconnects at least two of the plurality ofregions by applying, for example, a two dimensional method. The manuallyadjusted pixel intensities may be used as input data for the methoddiscussed herein. For example, two or more of the identified regions maybe triangulated by using, i.e., the Delaunay Triangulation method. Itmay be appreciated that other interconnection methods, i.e.,triangulation methods, may be used.

Intensity generation unit 208 generates intensity adjustments for atleast one pixel outside identified plurality of regions based on theinterconnection made by the interconnection unit and based on thereceived intensity adjustment through interpolation and/orextrapolation, for example. Interpolation and extrapolation may beperformed out by using, i.e., Barycentric interpolation/extrapolationmethod. It may be appreciated that other interpolation/extrapolationmethods may be used. The interpolation and extrapolation is performed tocalculate intensity adjusting factors for the remaining pixels on theimage based on the intensity adjusting factors received and adjusted inthe adjustment unit 204.

For example, if a pixel of a selected point has an intensity value of100000 on an original image A, as identified above, 200 on the tonemapped A′, as identified above, and 150 on the intensity adjusted imageA″, as identified above, the intensity adjusting factors for the pixelmay be determined to be 150/100000, which may be employed as input forthe interpolation/extrapolation process to calculate the intensityadjusting factors of those unselected pixels.

The intensity value of those unselected pixels may then be calculated byseverally multiplying the corresponding intensity adjusting factorsobtained from the interpolation/extrapolation process with the originalintensity value of the unselected pixels.

Intensity application unit 210 applies the intensity values determinedin the intensity generation unit 208 to the tone mapped image as for theunselected pixels so as to generate a resultant image. For example, theintensity values may be applied based on linear interpolation or otherhigh order interpolation, based on radial base functions, etc.

It may be appreciated that the functionality of the intensity generationunit 208 and intensity application unit 210 may be performed by usingOpenGL APIs provided at chip level so as to save processing time.

FIG. 3 illustrates a flow diagram of the method for processing imagedata performed by the computing device, according to an exampleembodiment. As shown in step S302, computing device 100 receivesinformation identifying of a plurality of regions within an originalimage A. The image may include unprocessed or RAW image data or mayinclude image data A′ that has been tone mapped.

The original image data A or image data A′ may be obtained from one ofstorage devices 150, received from a peripheral device 170, i.e., anexternal device, for example, an image capturing device, etc.

The receiving unit 202 then receives an intensity adjustment of at leastone of the identified plurality of regions (S604). The adjustment unit204 adjusts the intensities of at least one of the identified pluralityof regions based on the received intensity adjustment (S306) Theinterconnection unit 206 interconnects at least two of the plurality ofregions by applying a two-dimensional method (S308). The intensitygeneration unit 208 generates intensity adjustments for at least onepixel outside the plurality of regions based on the received intensityadjustment of at least one of the plurality of regions and theinterconnection of at least two of the plurality of regions (S310). Theintensity application unit 210 applies the generated intensityadjustments to the image to form a final image (S312).

It may be appreciated by one skilled in the art that further adjustmenton the pixels in the final image may be made. In other words, the flowin FIG. 3 may be repeated by implementing the final image as theoriginal image, wherein, in step 302, the plurality of regions areidentified in the final image and the adjustments are made based on theidentified plurality of regions in the final image. The steps depictedin FIG. 3 may be repeated any number of times until satisfying resultsare achieved.

FIGS. 4A-4C depicts an example of image processing according to anexample embodiment. As show in FIG. 4A, a tone mapped image is depicted.Regions 402 have been identified within the tone mapped image. Intensityadjustments 404 have been received with respect to each of theidentified images.

In FIG. 4B, interconnection of at least two of the identified regionsusing Delaunay Triangulation is performed. The intensity adjustments arecalculated for at least one of the pixels calculated outside theplurality of regions based on the triangulation and further based on theintensity adjustments 404. The pixels in the interconnected regions thathave been adjusted based on intensity adjustments are depicted in FIG.4B.

In FIG. 4C, the generated intensity adjustments are applied to the imagewherein intensity adjustments are applied for pixels outside theplurality of regions based on the interconnection and the receivedintensity adjustment. The pixels outside the interconnected regions thathave been adjusted are depicted in FIG. 4C.

There is little distinction left between hardware and softwareimplementations of aspects of systems; the use of hardware or softwareis generally (but not always, in that in certain contexts the choicebetween hardware and software can become significant) a design choicerepresenting cost vs. efficiency tradeoffs. There are various vehiclesby which processes and/or systems and/or other technologies describedherein can be effected (e.g., hardware, software, and/or firmware), andthat the preferred vehicle will vary with the context in which theprocesses and/or systems and/or other technologies are deployed. Forexample, if an implementer determines that speed and accuracy areparamount, the implementer may opt for a mainly hardware and/or firmwarevehicle; if flexibility is paramount, the implementer may opt for amainly software implementation; or, yet again alternatively, theimplementer may opt for some combination of hardware, software, and/orfirmware.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, those skilled in the art willrecognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure. In addition, those skilled in the art will appreciatethat the mechanisms of the subject matter described herein are capableof being distributed as a program product in a variety of forms, andthat an illustrative embodiment of the subject matter described hereinapplies regardless of the particular type of signal bearing medium usedto actually carry out the distribution. Examples of a signal bearingmedium include, but are not limited to, the following: a recordable typemedium such as a floppy disk, a hard disk drive, a Compact Disc (CD), aDigital Video Disk (DVD), a digital tape, a computer memory, etc.; and atransmission type medium such as a digital and/or an analogcommunication medium (e.g., a fiber optic cable, a waveguide, a wiredcommunications link, a wireless communication link, etc.).

Those skilled in the art will recognize that it is common within the artto describe devices and/or processes in the fashion set forth herein,and thereafter use engineering practices to integrate such describeddevices and/or processes into data processing systems. That is, at leasta portion of the devices and/or processes described herein can beintegrated into a data processing system via a reasonable amount ofexperimentation. Those having skill in the art will recognize that atypical data processing system generally includes one or more of asystem unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control motors (e.g., feedback forsensing position and/or velocity; control motors for moving and/oradjusting components and/or quantities). A typical data processingsystem may be implemented utilizing any suitable commercially availablecomponents, such as those typically found in datacomputing/communication and/or network computing/communication systems.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely examples, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected,” or“operably coupled,” to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable,” to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to disclosures containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations. In addition, evenif a specific number of an introduced claim recitation is explicitlyrecited, those skilled in the art will recognize that such recitationshould typically be interpreted to mean at least the recited number(e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those withinthe art that virtually any disjunctive word and/or phrase presenting twoor more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. A method comprising: receiving informationidentifying of a plurality of regions within an image, wherein each ofthe regions includes a group of pixels; receiving an intensityadjustment of at least one of the plurality of regions, wherein theintensity adjustment includes an adjustment of pixel intensity of the atleast one region; adjusting the pixel intensities of the at least oneplurality of regions based on the received intensity adjustment;interconnecting at least two of the plurality of regions by applying theadjusted pixel intensities to a two-dimensional method; generatingintensity adjustments for at least one pixel outside the plurality ofregions based on the received intensity adjustment of at least one ofthe plurality of regions and the interconnection of at least two of theplurality of regions; and applying the generated intensity adjustmentsto the image.
 2. The method of claim 1, wherein the received informationidentifies the plurality of regions in a tone mapped image.
 3. Themethod of claim 1, wherein at least one of the plurality of regions areone of a circle or square.
 4. The method of claim 1, wherein theintensity of at least one of the plurality of regions is linearlyadjusted.
 5. The method of claim 1, wherein the intensity of at leastone of the plurality of regions is non-linearly adjusted.
 6. The methodof claim 1, wherein the two dimensional method interconnecting at leasttwo of the plurality of regions is a linear function.
 7. The method ofclaim 6, wherein the two dimensional method is Delaunay triangulation.8. The method of claim 1, wherein the intensity adjustments aregenerated by an interpolation and extrapolation method.
 9. The method ofclaim 8, wherein the interpolation and extrapolation method is aBarycentric method.
 10. The method of claim 1, wherein the method isrepeatable with the adjusted image.
 11. An apparatus for intensitymapping of image data comprising: a receiver that receives informationidentifying of a plurality of regions within an image and receiving anintensity adjustment of at least one of the plurality of regions,wherein each of the regions includes a group of pixels, and whereinfurther the intensity adjustment includes an adjustment of pixelintensity of the at least one region; an adjustment unit that adjuststhe pixel intensities of the at least one plurality of regions based onthe received intensity adjustment; an interconnection unit thatinterconnects at least two of the plurality of regions by applying theadjusted pixel intensities to a two-dimensional method; an intensitygeneration unit that generates intensity adjustments for at least onepixel outside the plurality of regions based on the received intensityadjustment of at least one of the plurality of regions and theinterconnection of at least two of the plurality of regions; and anintensity application unit that applies the generated intensityadjustments to the image.
 12. The apparatus of claim 11, wherein thereceived information identifies the plurality of regions in a tonemapped image.
 13. The apparatus of claim 11, wherein at least one of theplurality of regions are one of a circle or square.
 14. The apparatus ofclaim 11, wherein the intensity of at least one of the plurality ofregions is linearly adjusted.
 15. The apparatus of claim 11, wherein theintensity of at least one of the plurality of regions is non-linearlyadjusted.
 16. The apparatus of claim 11, wherein the two dimensionalmethod interconnecting at least two of the plurality of regions is alinear function.
 17. The apparatus of claim 16, wherein the twodimensional method is Delaunay triangulation.
 18. The apparatus of claim11, wherein the intensity adjustments are generated by an interpolationand extrapolation method.
 19. The apparatus of claim 18, wherein theinterpolation and extrapolation method is a Barycentric method.
 20. Theapparatus of claim 11, wherein the method is repeatable with theadjusted image.